💹 Data Analysis & Modeling Repository Overview 💹

Within this repository is a collection of materials used in completing capstone projects and accredited certification in Data Analysis and Modeling. Please see below for the the principle areas of focus that highlight the key concepts, skills, and topics covered.

Principal Areas of Focus 🔦

• Statistical Experimentation
• Data Management/Validation
• Data Wrangling
• Product Sales Analysis
  • Most Advantageous Sales Method Types
  • Density Revenue Distribution by Sales Method
• Revenue Distribution
  • Revenue Distirubtion by Sales Methods
  • Revenue Distribution Overall Time Intervals
• Customer Insights
  • Customer distribution by sales_method applied to customer
  • Customer Website visits correlation to revenue
  • Customer distribution by years_as_customer
• Binning Customer Activities by Categorical Features
• Key Business Metric Identification
• Predictive Website Traffic Analysis
• Principal Component Analysis & Feature Selection
• Multiple Classification Model Generation & Accuracy Check

Tools Used 🧰

• SQL
• Python
• Pandas
• Seaborn
• Matplotlib
• Sklearn
  • StandardScaler
  • Logistic Regression
  • SVC
  • PCA
  • Model_Selection : (KFold, train_test_split, cross_val_score)
• Beautiful Soup (Web Scraping)
• Requests (API Library)
• IBM Cognos Dashboard

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Project Details & Certificate Issuers 🏗️

IBM Data Analyst

• Verification Link - IBM/Coursera

IBM provides a comprehensive learning path available through Coursera with a culminating capstone project which will be linked to below. Throughout the program, the curriculum offers labs, tests, exercises and ultimately the capstone project to bring together skills and tools that represent the most up-to-date practical skills and tools that data analysts use in their daily roles. Such ares of focus included

• Spreadsheets, Microsoft Excel
• Python Programming, Pandas, Numpy, Matplotlib
• SQL, Dashboard and BI Tools such as IBM Cognos Analytics
• Presentation Generation for Business Metrics and Stakeholder Review

Capstone : IBM 🪨

• Capstone Section Details
  • Section I : Data Collection, Web Scraping, Data Exploration
    • Section I
  • Section II : Data Wrangling (Duplicate Identification & Removal, Normalize and Impute Missing Values)
    • Section II
  • Section III : Data Analysis (Distribution of Data, Correlation Between Features, Outlier Detection and Removal)
    • Section III
  • Section IV : Data Visualization (Visualize Composition & Comparison of Data, Distribution of Data, Realtionship Between Features )
    • Section IV
• Cognos Dashboard
  • Project Highlights
    • Technology Usages by survery respondents for Programming Languages, Platforms, WebFrames
    • Future Technology Trend for survery respondents desire for ongoing skill/education development with respect to the same topics above
    • Demographics for survey respondents by Gender, Country, Age, & Education
  • Contains three sheets with differing visualization types
    • Bubble & Word Cloud Charts
    • Vertical & Horizontal Bar Charts
    • Pie & Line Charts
    • Geographic Density Map
  • Dashboard Link : IBM Cognos Project Dashboard
    • Github does include the _target attribute and thus this link will lead away from the repository listing in your current browser. Please use CTRL+click - PC or CMD+click - Mac to open this resource in a new tab
• Presentation Slides with Data Generated from Previous Sections
  • IBM Data Slides

Additional Section Learning Material

• Course details and logged materials highlighting the learning path for the course can be found as well
  • Specialization Course Details

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DataCamp

DataCamp offers various levels of certification for users of the platform to have their technical and reporting accumen put to the test to prove your skills are job-ready with Associate and Professional level certifications. DataCamp's coding challenges are free form, where candidates are presented with certain data but it is up to them to come up with an appropriate solution. The goal of this task is to demonstrate that the individual has the ability to perform the tasks required of them as a data analyst or scientist without being guided towards the appropriate solution.

Coding Challenges

• Data Analyst Professional

  • Coding Challenge : Data Analyst Challenge
  • Presentation / Powerpoint Material : Data Analyst Presentation Material
    • Within the presentation, the Business Goals & Objectives for the analysis work is detailed to add context for a mocked business task.
  • DataCamp Issued Professional Data Analyst Certificate : Data Analyst Certificate

• Data Science Professional

  • Coding Challenge : Data Science Challenge
  • Sample Business Request : Data Science Business Request
  • Presentation Material : Data Science Presentation Material
  • DataCamp Issued Professional Data Scientist Certificate : Data Science Certificate

Please visit the area's individual markdown file which contains details on the Exams administered by DataCamp for their certification requirements.

• DataCamp Root Project Materials

For Further Details on DataCamp's Certification Process

• https://app.datacamp.com/certification/resource-center/faq
• https://www.datacamp.com/blog/certificates-or-certification-which-should-you-choose

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